senior data analyst to h&m
2 weeks ago
Company Description
Sales is a global function within the H&M brand with the mission of growing and engaging our customer base, as well as growing and developing our sales channels. By holding the responsibility for our regions and bringing together expertise from both business and digital & tech perspectives, Sales plays a key role in delivering on our brand plan - to elevate H&M through product, experience, and brand providing aspirational fashion at an unbeatable price.
Job Description
We are now looking for a Senior Data Analyst to join the team. In the role you will be working closely with stakeholders and colleagues to address the most important topics on the agenda. More concretely, you will be using internal and external data to perform analysis on areas such store and online growth, customer behavior and store planning. You will be supporting the business with proactive analysis and decision support for strategic decisions and key initiatives, working together with other parts of the H&M Group to answer complex business questions. To succeed in the role you will need to take initiative, manage your own projects, communicate clearly with senior stakeholders and utilize your data analysis experience and business acumen to deliver actionable insights.
In the role you will:
- Work with a wide range of stakeholders within Retail, both globally and in our regions, to understand their analytical needs
- Transform business questions into analyses that result in actionable insights, working on the whole analysis process from defining the question to presenting the findings
- Analyze large data sets and select, test and develop the best method or model for your analysis, utilizing your technical skills in SQL, R, Python, Power BI or other analytics tools that can help you reach your goals
- Perform ad-hoc analyses to quickly address incoming questions when needed
- Support in leading analyses, deriving insights and preparing communication material for senior stakeholders
Qualifications
As a person we believe that you are a true role model of H&M values and that you are an ambitious, flexible and communicative team player, full of drive and optimism. You have a genuine passion for growing businesses and creating results. You have experience in driving strategically important analytical projects. You thrive in an entrepreneurial setting where you are constantly looking for possibilities to develop more efficient ways of working.
Additionally, we see that you:
- Have an academic degree in a quantitative field, such as engineering, business, economics, finance or math/statistics
- Have developed strong analytical skills through relevant work experience with at least four years of experience from Data Analyst, Insight Analyst or Business Analyst type roles
- Are confident in working with large data sets using SQL and extracting data by writing complex queries
- Are an expert in analyzing data in either R or Python
- Have strong business sense and have the ease of seeing the totality and making fast interpretations of data and other information
- Are a clear communicator who can easily translate complex analytical methods to business stakeholders and are comfortable in presenting results of your analyses to different stakeholders
- Are a team player and enjoy sharing your knowledge with colleagues
- Love data as much as we do and have a genuine interest in sharpening your analytical skills and creating business value out of data
Additional information
This is a permanent role, based in Stockholm. If you feel your experience, skills and ambitions are right for this role, please apply by sending your CV latest by 6th April 2025.
H&M Group is committed to creating a Diverse & Inclusive environment and we are actively looking for qualified candidates irrespective of race, gender, gender identity, sexual orientation, ethnicity, religion, national origin, disability, or age.
At H&M Group we strive to have a fair and inclusive recruitment process. We kindly ask you to not attach a cover letter in your application as they often contain information that can easily trigger unintentional biases.
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